Abstract
Considering the logical (Boolean or multi-valued) asynchronous framework, we delineate a reduction strategy for large signalling and regulatory networks. Consequently, focusing on the core network that drives the whole dynamics, we can check which attractors are reachable from given initial conditions, under fixed or varying environmental conditions.
More specifically, the dynamics of logical models are represented by (asynchronous) state transition graphs that grow exponentially with the number of model components. We introduce adequate reduction methods (preserving reachability of the attractors) and proceed with model-checking approaches.
Input nodes (that generally represent receptors) and output nodes (that constitute readouts of network behaviours) are each specifically processed to reduce the state space. The proposed approach is made available within GINsim, our software dedicated to the definition and analysis of logical models. The new GINsim functionalities consist in a proper reduction of output components, as well as the corresponding symbolic encoding of logical models for the NuSMV model checker. This encoding also includes a reduction over input components (transferring their values from states to transitions labels). Finally, we demonstrate the interest of the proposed methods through their application to a published large scale model of the signalling pathway involved in T cell activation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bilke, S., Sjunnesson, F.: Stability of the Kauffman model. Phys. Rev. E 65(016129) (2001)
Cimatti, A., Clarke, E., Giunchiglia, E., Giunchiglia, F., Pistore, M., Roveri, M., Sebastiani, R., Tacchella, A.: NuSMV 2: An OpenSource Tool for Symbolic Model Checking. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, pp. 359–364. Springer, Heidelberg (2002)
Clarke, E.M., Emerson, E.A., Sistla, A.P.: Automatic verification of finite-state concurrent systems using temporal logic specifications. ACM Trans. Program. Lang. Syst. 8, 244–263 (1986)
de Jong, H.: Modeling and simulation of genetic regulatory systems: a literature review. J. Comput Biol. 1(9), 67–103 (2002)
Fauré, A., Naldi, A., Chaouiya, C., Thieffry, D.: Dynamical analysis of a generic boolean model for the control of the mammalian cell cycle. Bioinformatics 22(14), 124–131 (2006)
Lomuscio, A., Pecheur, C., Raimondi, F.: Automatic verification of knowledge and time with nusmv. In: Veloso, M.M. (ed.) Proc. 20th Intl. Joint Conf. on Artificial Intelligence (IJCAI 2007), pp. 1384–1389. Morgan Kaufmann Publishers Inc. (2007)
Müller-Olm, M., Schmidt, D., Steffen, B.: Model-Checking: A Tutorial Introduction. In: Cortesi, A., Filé, G. (eds.) SAS 1999. LNCS, vol. 1694, pp. 330–354. Springer, Heidelberg (1999)
Monteiro, P.T., Chaouiya, C.: Efficient Verification for Logical Models of Regulatory Networks. In: Rocha, M.P., Luscombe, N., Fdez-Riverola, F., Rodríguez, J.M.C. (eds.) 6th International Conference on PACBB. AISC, vol. 154, pp. 259–267. Springer, Heidelberg (2012)
Naldi, A., Berenguier, D., Fauré, A., Lopez, F., Thieffry, D., Chaouiya, C.: Logical modelling of regulatory networks with GINsim 2.3. Biosystems 97(2), 134–139 (2009)
Naldi, A., Carneiro, J., Chaouiya, C., Thieffry, D.: Diversity and plasticity of th cell types predicted from regulatory network modelling. PLoS Comput. Biol. 6(9) (2010)
Naldi, A., Remy, E., Thieffry, D., Chaouiya, C.: Dynamically consistent reduction of logical regulatory graphs. Theor. Comput. Sci. 412, 2207–2218 (2011)
Naldi, A., Thieffry, D., Chaouiya, C.: Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 233–247. Springer, Heidelberg (2007)
Pecheur, C., Raimondi, F.: Symbolic Model Checking of Logics with Actions. In: Edelkamp, S., Lomuscio, A. (eds.) MoChArt IV. LNCS (LNAI), vol. 4428, pp. 113–128. Springer, Heidelberg (2007)
Remy, E., Ruet, P.: From minimal signed circuits to the dynamics of boolean regulatory networks. Bioinformatics 24(16), i220–i226 (2008)
Saadatpour, A., Albert, I., Albert, R.: Attractor analysis of asynchronous boolean models of signal transduction networks. J. Theor. Biol. 266(4), 641–656 (2010)
Saez-Rodriguez, J., Simeoni, L., Lindquist, J., Hemenway, R., Bommhardt, U., Arndt, B., Haus, U.-U., Weismantel, R., Gilles, E., Klamt, S., Schraven, B.: A logical model provides insights into T cell receptor signaling. PLoS Comput. Biol. 3(8), e163 (2007)
Saez-Rodriguez, J., Simeoni, L., Lindquist, J.A., Hemenway, R., Bommhardt, U., Arndt, B., Haus, U.-U., Weismantel, R., Gilles, E.D., Klamt, S., Schraven, B.: A logical model provides insights into T cell receptor signaling. PLoS Comput. Biol. 3(8), e163 (2007)
Schlitt, T., Brazma, A.: Current approaches to gene regulatory network modelling. BMC Bioinformatics 8(suppl. 6), S9 (2007)
Thieffry, D.: Dynamical roles of biological regulatory circuits. Brief. Bioinform. 8(4), 220–225 (2007)
Thomas, R.: Regulatory networks seen as asynchronous automata: A logical description. J. Theor. Biol. 153, 1–23 (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Naldi, A., Monteiro, P.T., Chaouiya, C. (2012). Efficient Handling of Large Signalling-Regulatory Networks by Focusing on Their Core Control. In: Gilbert, D., Heiner, M. (eds) Computational Methods in Systems Biology. CMSB 2012. Lecture Notes in Computer Science(), vol 7605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33636-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-33636-2_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33635-5
Online ISBN: 978-3-642-33636-2
eBook Packages: Computer ScienceComputer Science (R0)